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Systems for Autonomous Inspection - Enhancing Data Collection and Analysis Supervisors: Dr. Pawel Ladosc & Dr. Philip Zhao Year 1 MSc Course: MSc Robotics Year 2 – 4 PhD Location: The University
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and motivated theoretical biological physicists who ask how physical mechanisms shape functional biological patterns. We combine statistical physics, nonlinear dynamics, mathematical modeling and data
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; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine
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. Your work will focus on developing physics-informed AI methods to enhance decision-making in design and operation of next generation thermal energy storage systems, such as latent heat TES and
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at the intersection of cyber security, cyber-physical systems, and mathematical methods as part of the NORCICS Norwegian Centre for Cyber Security in Critical Sectors. The centre links researchers from
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ambitious graduate scientists and engineers who are keen to acquire new skills and have a desire to help increase use of RAS to help decarbonise the energy sector. You will become a pioneer and leader in
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data analysis, programming, and biology. You will be part of a collaborative research team with deep experimental and analytical expertise, with access to advanced tumor models and state-of-the-art
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collaboration with the co-supervisors and their labs, the project will also involve the use of these methods (and methods developed by others) for applications in infection biology, chiefly for designing
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, medical informatics, databases, data mining, machine learning, applied mathematics, biomedical modelling and analysis of complex networks. Joint data science projects between the different partners
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industry and its suppliers. Work duties This position as researcher is focused on developing digital solutions for the analysis and design of stormwater management systems. The position involves development